Abstract
Background
Diabetes mellitus (DM), chronic kidney disease (CKD), and advanced age are associated with poor outcomes in patients with acute coronary syndrome (ACS). This real-world study utilized data from the Taiwan Chang Gung Research Database (CGRD) to compare outcomes in ACS patients with DM, CKD, and the elderly.
Material/Methods
The study enrolled 28,613 ACS patients diagnosed based on CGRD medical records between January 2005 and December 2019. Baseline characteristics and clinical outcomes were compared among groups based on patient characteristics.
Results
Within the ACS cohort, 42.1% had DM, 48.2% had CKD, and 33.6% were elderly. Among them, 10.7% (3,070) were elderly patients with both DM and CKD. Elderly patients with DM and CKD had significantly higher risks of gastrointestinal bleeding (hazard ratio=11.32), cardiovascular events (HR=7.29), and all-cause mortality (HR=8.59). Patients with three or at least two of these risk factors had a 2.20–2.99-fold increased risk of recurrent ACS during the three-year follow-up period..
Conclusions
Patients with the combination of DM, CKD, and advanced age (elderly) experienced an 11.32-fold increased risk of gastrointestinal bleeding, 7.29-fold increased risk of cardiovascular events, and 8.59-fold increased risk of all-cause mortality compared to those without these risk factors. Furthermore, patients with two or more of these risk factors had a 2- to 3-fold increased risk of recurrent ACS. These findings emphasize the importance of managing multiple risk factors in ACS patients to improve outcomes.
Keywords: Acute Coronary Syndrome; Diabetes Mellitus; Frail Elderly; Prognosis; Renal Insufficiency, Chronic
Background
Acute coronary syndrome (ACS) refers to acute myocardial ischemia and/or infarction due to various degrees of coronary blood flow reduction due to plaque rupture/erosion and thrombosis formation or supply and demand mismatch; ACS presents as unstable angina, non-ST-segment elevation myocardial infarction (NSTEMI), and ST-segment elevation myocardial infarction (STEMI) [1]. In the current aging society, ACS is still a major health problem, especially in the elderly population [2]. Elderly patients continue to be at high risk of poor prognosis, are less likely to receive evidence-based care, and have high mortality rates regardless of evidence-based care [3–6]. Advanced age, chronic kidney disease (CKD), diabetes mellitus (DM), multiple vessel disease, partial revascularization, and hemodynamic instability were predictive factors for mortality among patients with ACS [3,7–9]. In the Asian population with ACS, TIMI and GRACE risk scores demonstrated good predictive accuracies, but most studies only focused on the patients with STEMI and short-term prognosis [10,11]. In elderly patients with ACS, 2 of the most common comorbidities are DM and CKD, affecting 20% to 30% of this population [12]. However, few large cohort studies have reported the impact of DM, CKD, and advanced age on the prognosis of Asian patients with ACS.
The Chang Gung Research Database (CGRD) is a database derived from the original medical records of Chang Gung Memorial Hospital (CGMH), which comprises 7 medical institutes spanning from the northeast to southern regions of Taiwan. CGMH, with its 10 070 beds, admits over 280 000 patients annually. Moreover, the CGRD is a multi-institutional, original medical record-based research database that offers extensive overall and disease-specific coverage of Taiwan. It is worth noting that the CGRD exhibits significantly higher severity of comorbidities [13,14]. Studies conducted using the CGRD have been recognized for their high quality and positive impact on healthcare in Taiwan. Notably, the CGRD has been utilized for ACS research to explore the effects of conduction delay and the prognosis of real-world lipid control [15,16].
Therefore, this real-world study used data from the Taiwan CGRD to compare outcomes in patients with ACS, DM, CKD, and advanced age.
Material and Methods
Ethics Statement
This retrospective study was approved for human research by the Institutional Review Committee of the Kaohsiung Chang Gung Memorial Hospital (number: 202101103B0) and conformed to the guidelines of the 1975 Declaration of Helsinki. Informed consent was waived because of the retrospective nature of the study and the use of anonymous clinical data in the analysis.
Patient Population and Groups
Patients diagnosed with ACS from January 2005 to December 2019 were recruited and their medical history was obtained from the CGRD, which is the largest healthcare system in Taiwan.
The inclusion criteria were age ≥18 years and a diagnosis of ACS (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] code 410.xx, 411.xx, and 412.xx, or Tenth Revision [ICD-10] codes I20, I21, and I22). Patients were divided into DM, non-DM, CKD, non-CKD, elderly, and non-elderly groups according to comorbidities and age. CKD was defined as a creatinine clearance (Cockcroft-Gault equation) <60 mL/min. Elderly patients were defined as those aged >75 years old.
Baseline and Outcome Variables
Data on general demographics, comorbidities, medication use, gastrointestinal (GI) bleeding, recurrent ACS, cardiovascular (CV) mortality, and all-cause mortality of patients were obtained and compared between the groups with or without risk factors.
Definitions
GI bleeding was defined as an episode of coffee ground emesis, hematemesis, melena, or red blood per rectum occurring after an ACS episode and documented by the treating physician [17]. ACS was defined as any group of clinical symptoms compatible with acute myocardial ischemia, and included UA, NSTEMI, and STEMI. CV mortality was defined as CV-related death. All-cause mortality was defined as death from any cause of death.
Study Endpoints
Study endpoints were GI bleeding, recurrent ACS, CV mortality, and all-cause mortality.
Statistical Analyses
Data are presented as mean±standard deviation or numbers (percentages) for descriptive statistics. Clinical characteristics of the 2 groups were compared using the independent sample t test and the chi-square test for categorical variables. Kaplan-Meier curve analysis and hazard ratios (HR) with 95% confidence intervals (CI) were performed using the log-rank test and Cox regression method for GI bleeding, recurrent ACS, CV mortality, and all-cause mortality in the groups during the 3-year follow-up period. Statistical significance was set at P<0.05. All analyses were performed using SAS version 9.4 (SAS Institute. Inc., Cary, NC, USA).
Results
Comparison of Baseline Characteristics Between Patients with and without DM
This study enrolled 28 163 participants; baseline characteristics and medications are shown in Table 1. Between non-DM (57.9%) and DM (42.1%) populations, older age (non-DM vs DM; 66.02±14.68 years old vs 67.98±12.25 years old; P<0.001), lower prevalence of males (non-DM vs DM; 73.47% vs 62.89%; P<0.001), and higher body mass index (BMI) (non-DM vs DM; 24.67±4.31 kg/m2 vs 25.20±4.42 kg/m2; P<0.001) presented in patients with DM. A significantly higher prevalence of comorbidities, except for chronic obstructive pulmonary disease and smoking, was noted when DM was compared with the non-DM population. A higher prevalence of clopidogrel use and shorter follow-up period were noted in patients with DM.
Table 1.
Baseline characteristics in the patients.
| Variable | DM | CKD | Elderly | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Non-DM | DM | P value | Non-CKD | CKD | P value | Non-elderly | Elderly | P value | |
| Number | 16743 | 11870 | 14019 | 14594 | 19155 | 9458 | |||
| General demographics | |||||||||
| Age (years) | 66.02 ±14.68 | 67.98 ±12.25 | <0.001 | 61.69 ±13.50 | 71.77 ±12.10 | <0.001 | 59.41 ±10.17 | 81.86 ±5.10 | <0.001 |
| Male sex (%) | 12301 (73.47) | 7465 (62.89) | <0.001 | 10692 (76.27) | 9074 (62.18) | <0.001 | 14519 (75.80) | 5247 (55.48) | <0.001 |
| BMI (kg/m2) | 24.67 ±4.31 | 25.20 ±4.42 | <0.001 | 25.38 ±4.41 | 24.44 ±4.28 | <0.001 | 25.65 ±4.27 | 23.26 ±4.08 | <0.001 |
| Comorbidities | |||||||||
| Diabetes mellitus (%) | 0 (0) | 11870 (100) | <0.001 | 4186 (29.86) | 6261 (42.90) | <0.001 | 7221 (37.70) | 3226 (34.11) | <0.001 |
| Hypertension (%) | 8142 (48.63) | 7850 (66.13) | <0.001 | 7067 (50.41) | 8925 (61.16) | <0.001 | 10521 (54.93) | 5471 (57.85) | <0.001 |
| PAOD (%) | 64 (0.38) | 128 (1.08) | <0.001 | 54 (0.39) | 138 (0.95) | <0.001 | 120 (0.63) | 72 (0.76) | 0.189 |
| COPD (%) | 995 (5.94) | 535 (4.51) | <0.001 | 602 (4.29) | 928 (6.36) | <0.001 | 591 (3.09) | 939 (9.93) | <0.001 |
| ESRD (%) | 805 (4.81) | 1344 (11.32) | <0.001 | 0 (0) | 2099 (14.38) | <0.001 | 1194 (6.23) | 955 (10.10) | <0.001 |
| Smoking (%) | 2906 (17.36) | 1298 (10.94) | <0.001 | 2790 (19.90) | 1414 (9.69) | <0.001 | 3551 (18.54) | 653 (6.90) | <0.001 |
| Liver cirrhosis (%) | 231 (1.38) | 232 (1.95) | 0.001 | 185 (1.32) | 278 (1.90) | <0.001 | 311 (1.62) | 152 (1.61) | 0.917 |
| Prior GI bleeding (%) | 1621 (9.68) | 1604 (13.51) | <0.001 | 737 (5.26) | 2488 (17.05) | <0.001 | 1481 (7.73) | 1744 (18.44) | <0.001 |
| Prior stroke (%) | 1029 (6.15) | 1081 (9.11) | <0.001 | 777 (5.54) | 1333 (9.13) | <0.001 | 1134 (5.92) | 976 (10.32) | <0.001 |
| Medication | |||||||||
| Antiplatelet agent | |||||||||
| Aspirin (%) | 10730 (64.09) | 7629 (64.27) | 0.748 | 10368 (73.96) | 7991 (54.76) | <0.001 | 13680 (71.42) | 4679 (49.47) | <0.001 |
| Clopidogrel (%) | 8761 (52.33) | 6489 (54.67) | 0.001 | 7927 (56.54) | 7323 (50.18) | <0.001 | 10759 (56.17) | 4491 (47.48) | <0.001 |
| Ticagrelor (%) | 2203 (13.16) | 1502 (12.65) | 0.211 | 2539 (18.11) | 1166 (7.99) | <0.001 | 3193 (16.67) | 512 (5.41) | <0.001 |
| F/U period (years) | 2.0 ±1.2 | 1.9 ±1.2 | <0.001 | 2.3 ±1.0 | 1.6 ±1.3 | <0.001 | 2.2 ±1.1 | 1.5 ±1.3 | <0.001 |
Data are expressed as mean (standard deviation) or as number (percentage). BMI – body mass index; PAOD – peripheral arterial occlusive disease; COPD – chronic obstructive pulmonary disease; ESRD – end-stage renal disease; GI – gastrointestinal; F/U – follow-up.
Comparison of Baseline Characteristics Between Patients with and without CKD
Between non-CKD (51.8%) and CKD (48.2%) populations, older age (non-CKD vs CKD; 61.69±13.50 years old vs 71.77±12.10 years old; P<0.001), lower prevalence of male sex (non-CKD vs CKD; 76.27% vs 62.18%; P<0.001), and lower BMI (non-CKD vs CKD; 25.38±4.41 kg/m2 vs 24.44±4.28 kg/m2; P<0.001) presented in patients with CKD. A significantly higher prevalence of comorbidities, except smoking, was noted when CKD patients were compared with the non-CKD population. A lower prevalence of aspirin, clopidogrel, and ticagrelor use and shorter follow-up period were noted in patients with CKD.
Comparison of Baseline Characteristics Between Non-Elderly and Elderly Patients
Between non-elderly (66.4%) and elderly (33.6%) populations, older age (non-elderly vs elderly; 59.41±10.17 years old vs 81.86±5.10 years old; P<0.001), lower prevalence of male sex (non-elderly vs elderly; 75.80% vs 55.48%; P<0.001), and lower BMI (non-elderly vs elderly; 25.65±4.27 kg/m2 vs 23.26±4.08 kg/m2; P<0.001) presented in elderly patients. A significantly higher prevalence of comorbidities, except DM and smoking, was noted in the elderly than in the non-elderly population. The prevalence of peripheral arterial occlusive disease and liver cirrhosis was similar between the non-elderly and elderly groups. A lower prevalence of aspirin, clopidogrel, and ticagrelor use and a shorter follow-up period were noted in elderly patients.
Kaplan-Meier Curve Analysis and HRs for GI Bleeding in Patients with Different Risk Factors During the 3-Year Follow-Up Period
Figure 1A shows the Kaplan-Meier curve analysis for GI bleeding between the ACS population with DM, CKD, or advanced age, or the combination of 2 or 3 risk factors (log-rank P<0.001).
Figure 1.
Kaplan-Meier curve analysis and hazard ratios (HRs) for gastrointestinal (GI) bleeding in patients with acute coronary syndrome (ACS) and a combination of diabetes mellitus (DM), chronic kidney disease (CKD), or advanced age during the 3-year follow-up period. (A) Kaplan-Meier curve analysis for GI bleeding between the ACS population with DM, CKD, or advanced age, or the combination of 2 or 3 risk factors (log-rank P<0.001). (B) In patients with 1 risk factor (DM, CKD, or elderly age), the HR of GI bleeding was 1.87 (95% CI: 1.48–2.35; P<0.001), 3.39 (95% CI: 2.74–4.18; P<0.001), and 4.33 (95% CI: 3.42–5.50; P<0.001), respectively. In patients with a combination of 2 risk factors, the HR of GI bleeding was 6.83 (95% CI: 5.26–8.86; P<0.001) for elderly age plus DM, 3.39 (95% CI: 6.58–9.60; P<0.001) for CKD plus elderly age, 6.21 (95% CI: 5.17–7.45; P<0.001) for CKD plus DM. In elderly patients with DM and CKD, HR of GI bleeding was 11.32 (95% CI: 9.41–13.61; P<0.001) during the 3-year follow-up period.
In patients with 1 risk factor (DM, CKD, or age; Figure 1B), the HRs of GI bleeding were 1.87 (95% CI: 1.48–2.35; P<0.001), 3.39 (95% CI: 2.74–4.18; P<0.001), and 4.33 (95% CI: 3.42–5.50; P<0.001), respectively. In the patients with a combination of 2 risk factors, the HR of GI bleeding was 6.83 (95% CI: 5.26–8.86; P<0.001) for advanced age plus DM, 3.39 (95% CI: 6.58–9.60; P<0.001) for CKD plus advanced age, and 6.21 (95% CI: 5.17–7.45; P<0.001) for CKD plus DM. In elderly patients with DM and CKD, the HR of GI bleeding was 11.32 (95% CI: 9.41–13.61; P<0.001) during the 3-year follow-up period.
Kaplan-Meier Curve Analysis and HRs for Recurrent ACS in Patients With Different Risk Factors During the 3-Year Follow-Up Period
Figure 2A shows the Kaplan-Meier curve analysis for recurrent ACS between the ACS population with DM, CKD, or advanced age, or the combination of 2 or 3 risk factors (log-rank P<0.001).
Figure 2.
Kaplan-Meier curve analysis and hazard ratios (HRs) for recurrent acute coronary syndrome (ACS) in patients with ACS and a combination of diabetes mellitus (DM), or chronic kidney disease (CKD), or advanced age during the 3-year follow-up period. (A) Kaplan-Meier curve analysis for recurrent ACS between the ACS population with DM, CKD, or advanced age, or the combination of 2 or 3 risk factors (log-rank P<0.001). (B) In patients with 1 risk factor (DM, CKD, or advanced age), the HR of recurrent ACS was 1.13 (95% CI: 0.99–1.29; P=0.070), 1.63 (95% CI: 1.44–1.85; P<0.001), and 1.62 (95% CI: 1.38–1.91; P<0.001), respectively. In patients with a combination of 2 risk factors, the HR of recurrent ACS was 2.20 (95% CI: 1.81–2.67; P<0.001) for advanced age plus DM, 2.35 (95% CI: 2.08–2.66; P<0.001) for CKD plus advanced age, and 2.72 (95% CI: 2.45–3.03; P<0.001) for CKD plus DM. In elderly patients with DM and CKD, the HR of recurrent ACS was 2.99 (95% CI: 2.65–3.37; P<0.001) during the 3-year follow-up period.
In patients with 1 risk factor (DM, CKD, or age; Figure 2B), the HRs of recurrent ACS were 1.13 (95% CI: 0.99–1.29; P=0.070), 1.63 (95% CI: 1.44–1.85; P<0.001), and 1.62 (95% CI: 1.38–1.91; P<0.001), respectively. In patients with a combination of 2 risk factors, the HR of recurrent ACS was 2.20 (95% CI: 1.81–2.67; P<0.001) for advanced age plus DM, 2.35 (95% CI: 2.08–2.66; P<0.001) for CKD plus advanced age, 2.72 (95% CI: 2.45–3.03; P<0.001) for CKD plus DM. In elderly patients with DM and CKD, the HR of recurrent ACS was 2.99 (95% CI: 2.65–3.37; P<0.001) during the 3-year follow-up period.
Kaplan-Meier Curve Analysis and HR for CV Mortality in Patients With Different Risk Factors During the 3-Year Follow-Up Period
Figure 3A shows the Kaplan-Meier curve analysis for CV mortality between the ACS population with DM, CKD, or advanced age, or the combination of 2 or 3 risk factors (log-rank P<0.001).
Figure 3.
Kaplan-Meier curve analysis and hazard ratios (HRs) for cardiovascular (CV) mortality in patients with acute coronary syndrome (ACS) and a combination of diabetes mellitus (DM), or chronic kidney disease (CKD), or advanced age during the 3-year follow-up period. (A) Kaplan-Meier curve analysis for CV mortality between the ACS population with DM, CKD, or advanced age, or the combination of 2 or 3 risk factors (log-rank P<0.001). (B) In patients with 1 risk factor (DM, CKD, or advanced age), HR of CV mortality was 1.19 (95% CI: 1.00–1.42; P=0.057), 4.43 (95% CI: 3.88–5.05; P<0.001), and 4.47 (95% CI: 3.84–5.21; P<0.001), respectively. In patients with combination of two risk factors, HR of CV mortality was 4.53 (95% CI: 3.74–5.49; P<0.001) for advanced age plus DM, 8.76 (95% CI: 7.76–9.89; P<0.001) for CKD plus advanced age, and 4.17 (95% CI: 3.66–4.74; P<0.001) for CKD plus DM. In elderly patients with DM and CKD, HR of CV mortality was 7.29 (95% CI: 6.42–8.29; P<0.001) during the 3-year follow-up period.
In patients with 1 risk factor (DM, CKD, or age; Figure 3B), the HRs of CV mortality were 1.19 (95% CI: 1.00–1.42; P=0.057), 4.43 (95% CI: 3.88–5.05; P<0.001), and 4.47 (95% CI: 3.84–5.21; P<0.001), respectively. In patients with a combination of 2 risk factors, the HR of CV mortality was 4.53 (95% CI: 3.74–5.49; P<0.001) for advanced age plus DM, 8.76 (95% CI: 7.76–9.89; P<0.001) for CKD plus advanced age, and 4.17 (95% CI: 3.66–4.74; P<0.001) for CKD plus DM. In elderly patients with DM and CKD, the HR of CV mortality was 7.29 (95% CI: 6.42–8.29; P<0.001) during the 3-year follow-up period.
Kaplan-Meier Curve Analysis and HR for All-Cause Mortality in the Patients With Different Risk Factors During the 3-Year Follow-Up Period
Figure 4A shows the Kaplan-Meier curve analysis for all-cause mortality between the ACS population with DM, CKD, or advanced age, or the combination of 2 or 3 risk factors (log-rank P<0.001).
Figure 4.
Kaplan-Meier curve analysis and hazard ratios (HRs) for all-cause mortality in patients with acute coronary syndrome (ACS) and a combination of diabetes mellitus (DM), or chronic kidney disease (CKD), or advanced age during the 3-year follow-up period. (A) Kaplan-Meier curve analysis for all-cause mortality between the ACS population with DM, CKD, or advanced age, or the combination of 2 or 3 risk factors (log-rank P<0.001). (B) In patients with 1 risk factor (DM, CKD, or advanced age), HR of all-cause mortality was 1.37 (95% CI: 1.23–1.52; P<0.001), 3.92 (95% CI: 3.60–4.27; P<0.001), and 5.05 (95% CI: 4.60–5.55; P<0.001), respectively. In the patients with a combination of two risk factors, HR of all-cause mortality was 5.30 (95% CI: 4.72–5.95; P<0.001) for advanced age plus DM, 8.27 (95% CI: 7.66–8.94; P<0.001) for CKD plus advanced age, and 4.75 (95% CI: 4.39–5.15; P<0.001) for CKD plus DM. In elderly patients with DM and CKD, the HR of CV mortality was 8.59 (95% CI: 7.94–9.30; P<0.001) during the 3-year follow-up period.
In patients with 1 risk factor (DM, CKD, or age; Figure 4B), the HR of all-cause mortality was 1.37 (95% CI: 1.23–1.52; P<0.001), 3.92 (95% CI: 3.60–4.27; P<0.001), and 5.05 (95% CI: 4.60–5.55; P<0.001), respectively. In patients with combination of 2 risk factors, the HR of all-cause mortality was 5.30 (95% CI: 4.72–5.95; P<0.001) for advanced age plus DM, 8.27 (95% CI: 7.66–8.94; P<0.001) for CKD plus advanced age, and 4.75 (95% CI: 4.39–5.15; P<0.001) for CKD plus DM. In elderly patients with DM and CKD, the HR of CV mortality was 8.59 (95% CI: 7.94–9.30; P<0.001) during the 3-year follow-up period.
Discussion
In our ACS cohort, 42.1% of patients had DM, 48.2% had CKD, 33.6% were elderly, and 10.7% (3070) were elderly patients with DM and CKD. Elderly patients with DM and CKD had a very high risk of GI bleeding (HR=11.32), CV (HR=7.29), and all-cause mortality (HR=8.59). Patients with a combination 2 or 3 risk factors had a similar risk of recurrent ACS during the 3-year follow-up period. DM, CKD, and advanced age are important factors related to mortality in the ACS population [3,18,19]. In patients with ACS, a gradient of risk has been observed based on the presence or absence of DM and CKD, with those having both risk factors being at the highest risk [20]. However, there have been no studies that have examined the combination of all 3 risk factors, including DM, CKD, and advanced age, and were specifically focused on the prognosis of this combination in the ACS population. In our study, DM had a non-significant trend of CV mortality, and CKD and advanced age had ≥4-fold risk of CV mortality. DM had a 1.37-fold higher risk of all-cause mortality, CKD had a 3.92-fold higher risk of all-cause mortality, and advanced age had a 5.05-fold higher risk of all-cause mortality. Patients with a combination of DM, CKD, and advanced age had a 7.29-fold risk of CV mortality and an 8.59-fold risk of all-cause mortality during the 3-year follow-up period.
According to the European ACS report, 21% of patients with STEMI and 27% with NSTEMI have established or newly discovered DM, and those with DM have worse clinical outcomes than those without [21,22]. In the Asian population with STEMI and ACS, the prevalence of DM is estimated to be 27% to 35%, seemingly higher than that of European population [23–25]. From large registries, CKD prevalence was approximately 30% to 40% in Asian and European patients with ACS [23,26,27]. Aging is also accompanied by decreased creatinine production, according to the Cockcroft-Gault equation. According to a previous study on elderly patients with ACS, approximately 80% had a creatinine clearance of less than 60 mL/min [28].
GI bleeding is common in patients with ACS, particularly under dual antiplatelet therapy and high-potency antiplatelet agents. In previous studies, the incidence of bleeding complications occurred in approximately one-third of patients discharged on dual antiplatelet therapy, and the incidence of GI bleeding was estimated to be 0.25% to 7.63% [29]. GI bleeding plays an important role in the prognosis of patients with ACS, and DM, CKD, and advanced age are important factors of bleeding complications and GI bleeding [30,31]. Bleeding events can impact duration and potency of antiplatelet therapy use. However, most randomized controlled trials have excluded patients aged ≥75 years with CKD. In our study, advanced age was related to the strongest HR (4.33) of GI bleeding, and advanced patients with DM and CKD had an 11.32-fold higher risk of GI bleeding.
DM is a coronary artery disease-equivalent condition, and the combination of DM and coronary artery disease still represents a major challenge for clinicians, even with broad developments in pharmacotherapy and revascularization techniques [32,33]. DM and CKD were found to be the important independent predictors of recurrent acute myocardial infarction after successful intervention for the first ischemic event [34,35]. In our study, DM achieved a non-significant trend of recurrent ACS and CKD, and advanced age presented an approximately 1.6-fold risk of recurrent ACS. Patients with a combination of 2 or 3 risk factors had 2.20- to 2.99-fold risk of recurrent ACS.
Study Limitations
This study had the limitations of having a retrospective study design and obtaining patient information from medical records. The study focused on the risk factors of DM, CKD, and advanced age and did not explore the effect of coronary artery disease and left ventricular performance severity. We also did not explore the effect of different medical treatments. Nevertheless, our results provide valuable information regarding important factors, including DM, CKD, and advanced age, and the associated clinical outcomes in patients with ACS.
Conclusions
In patients with 3 risk factors (DM, CKD, and advanced age), there was an 11.32-fold increased risk of GI bleeding, 7.29-fold increased risk of CV mortality, and 8.59-fold increased risk of all-cause mortality compared to the population without DM, CKD, and advanced age. Additionally, patients with 2 or more risk factors had a 2- to 3-fold increased risk of recurrent ACS than the population without DM, CKD, and advanced age.
Acknowledgments
The authors thank Yi-Hsuan Tsai for the statistical assistance and acknowledge the support of the Biostatistics Center of Kaohsiung Chang Gung Memorial Hospital (Grant CORPG8L0591) for the study design, monitoring, data analysis, and interpretation.
Footnotes
Conflict of interest: None declared
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher
Declaration of Figures’ Authenticity
All figures submitted have been created by the authors, who confirm that the images are original with no duplication and have not been previously published in whole or in part.
Financial support: This study was supported by the research program of Kaohsiung Chang Gung Memorial Hospital (Grant CORPG8L0591)
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